The critics of “hereditarianism” often claim that any attempt to explain human behavior by invoking genes is confronted with insurmountable methodological difficulties. They reject the idea that heritability estimates could lead to genetic explanations by pointing out that these estimates are strictly valid only for a given population and that they are exposed to the irremovable confounding effects of genotype-environment interaction and genotype-environment correlation. I argue that these difficulties are greatly exaggerated, and that we would be wrong to regard them as presenting a fundamental obstacle to the search for genetic explanations. I also show that, to the extent they are cogent, these objections may prove to be even more damaging to the “environmentalist” standpoint.

The article responds to some of the points raised by B. van Fraassen concerning probability kinematics and direct inference within the framework of the approach to the revision of probability judgment proposed by Levi in The Enterprise of Knowledge. In particular, the critical importance of the question of direct inference is emphasized and explained.

Research on diseases such as cancer reveals that primary mechanisms, which have been the focus of study by the new mechanists in philosophy of science, are often subject to control by other mechanisms. Cancer cells employ the same primary mechanisms as healthy cells but control them differently. I use cancer research to highlight just how widespread control is in individual cells. To provide a framework for understanding control, I reconceptualize mechanisms as imposing constraints on flows of free energy, with control mechanisms operating on flexible constraints in primary mechanisms. I argue that control mechanisms themselves often form complex, integrated networks.

Leuridan argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and he advocates Mitchell's pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong among mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain.

A hallmark of ecological research is dealing with complexity in the systems under investigation. One strategy is to diminish this complexity by constructing models and theories that are general. Alternatively, ecologists can constrain the scope of their generalizations to particular phenomena or types of systems. However, research employing the second strategy is often met with scathing criticism. I offer a theoretical argument in support of moderate generalizations in ecological research, based on the notions of interdependence and causal heterogeneity and their effect on the trade-off between generality and realism.

Popper distinguishes the problems of theoretical and pragmatic preference between rival theories, but he claims that there is a common non-inductive solution to both of them, viz. the “best-tested theory”, or the theory with the highest degree of corroboration. He further suggests that the degrees of corroboration serve as indicators of verisimilitude. One may therefore raise the question whether the recent theory of verisimilitude gives a general non-inductive solution to the problem of theoretical preference. This paper argues that this is not the case: the theory of verisimilitude is applicable to this problem if and only if there is an independent solution to the problem of induction. Moreover, the solutions to the theoretical and pragmatic problems of preference coincide only in some special cases.

We critically examine Denis Walsh's latest attack on the causalist view of fitness. Relying on Judea Pearl's Sure-Thing Principle and geneticist John Gillespie's model for fitness, Walsh has argued that the causal interpretation of fitness results in a reductio. We show that his conclusion only follows from misuse of the models, that is, (1) the disregard of the real biological bearing of the population-size parameter in Gillespie's model and (2) the confusion of the distinction between ordinary probability and Pearl's causal probability. Properly understood, the models used by Walsh do not threaten the causalist view of fitness.

Typically, the imagination in thought experiments has been taken to consist in mental images; we visualize the state of affairs described. A recent alternative from Fiora Salis and Roman Frigg maintains that it is only the propositional imagination that is necessary for the conduct of a thought experiment. I set out problems with these monistic accounts and develop a pluralist stance. Thought experiments appeal to a variety of our imaginative capacities, and we ought to focus on the function of particular thought experiments when considering what type of imaginative engagement they invite.

The idea that rational agents should have acyclic preferences and should obey conditionalization has been defended on the grounds that otherwise an agent is threatened with becoming a “money pump.” This essay argues that such arguments fail to prove their claims.

What are the functional units of the brain? If the function of the brain is to process information-carrying signals, then the functional units will be the senders and receivers of those signals. Neurons have been the default candidate, with action potentials as the signals. But there are alternatives: synapses fit the action potential picture more cleanly, and glial activities (e.g., in astrocytes) might also be characterized as signaling. Are synapses or nonneuronal cells better candidates to play the role of functional units? Will informational signaling still be the best model for brain function if we move beyond the neuron doctrine?

Most models of generational succession in sexually reproducing populations necessarily move back and forth between genic and genotypic spaces. We show that transitions between and within these spaces are usually hidden by unstated assumptions about processes in these spaces. We also examine a widely endorsed claim regarding the mathematical equivalence of kin-, group-, individual-, and allelic-selection models made by Lee Dugatkin and Kern Reeve. We show that the claimed mathematical equivalence of the models does not hold.

In this rejoinder to the three preceding comments, I provide some additional philosophical warrant for the biomedical sciences' focus on model organisms. I then relate the inquiries on model systems to the concept of ‘deep homology’, and indicate that the issues that appear to divide my commentators and myself are in part empirical ones. I cite recent work on model organisms, and especially C. elegans that supports my views. Finally, I briefly readdress some of the issues raised by Developmental Systems Theory.

I criticize conceptual pluralism, as endorsed recently by John Dupré and Philip Kitcher, for failing to supply strategies for demarcating science from non-science. Using creation-science as a test case, I argue that pluralism blocks arguments that keep creation-science in check and that metaphysical pluralism offers it positive, metaphysical support. Logical empiricism, however, still provides useful resources to reconfigure and manage the problem of creation-science in those practical and political contexts where pluralism will fail.

There is often substantial disparity between philosophical ideals and scientific practice. Philosophical reductionism is motivated by a drive for ontological austerity. The vehicle is conceptual parsimony: the fewer our conceptual primitives, the less are our ontological commitments. A general moral to be drawn from my “Functionalism and Reductionism” (1979) is that scientific reduction does not, and should not be expected to, facilitate conceptual economy; yet reduction it still is, and in the classical mold. Those who press for the irreducibility of a functional psychology have been seduced by an inadequate account of scientific reduction. Patricia Kitcher (1980) is unhappy with my argument because it fails to live up to her philosophical ideals. “The claim that psychology is irreducible to neurophysiology,” she suggests, “rests to a large extent on the fact that, even in principle, neurophysiology is not capable of carrying out the explanatory work of a functional psychology” (1980, p. 140).

A brief discussion is offered of what it means to say that a set of statements provides D-N explanation with special emphasis given to approximative D-N explanation. An idealized theory is seen to provide approximative D-N explanation. An ideal case provides explanation only if postulates are offered which connect the ideal antecedent condition with actual conditions. Such postulates will help in accounting for deviations between what the consequent of the ideal case entails and what actually occurs. Three ways are presented for deciding on the acceptability of idealizations: (i) as actual conditions more closely approximate the ideal antecedent conditions specified in an ideal case, the more closely actual cases ought to approximate the consequent of the ideal case; (ii) the additional postulates connecting ideal antecedent conditions with actual conditions ought to account for deviations between what is entailed by an idealized theory and what actually occurs ; and (iii) an idealized theory is explained by a more general theory when certain state variables in the more general theory are given extreme values. It is argued that (iii) is not a necessary condition for the acceptability of idealizations.

In three recent papers, Wayne Myrvold (1996, 2003) and Timothy McGrew (2003) have developed Bayesian accounts of the virtue of unification. In his account, McGrew demonstrates that, ceteris paribus, a hypothesis that unifies its evidence will have a higher posterior probability than a hypothesis that does not. Myrvold, on the other hand, offers a specific measure of unification that can be applied to individual hypotheses. He argues that one must account for this measure in order to calculate correctly the degree of confirmation that a hypothesis receives from its evidence. Using the probability calculus, I prove that the two accounts of unification require the same underlying inequality; thus, McGrew and Myrvold have accounted for unification in fundamentally identical probabilistic terms. I then evaluate five putative counterexamples to this account and show that these examples, far from disqualifying it, serve to clarify our notion of unification by disentangling it from a host of other concepts.

This article offers a critique of an account of explanatory integration that claims that explanations of cognitive capacities by functional analyses and mechanistic explanations can be seamlessly integrated. It is shown that achieving such explanatory integration requires that the terms designating cognitive capacities in the two forms of explanation are stable but that experimental practice in the mind-brain sciences currently is not directed at achieving such stability. A positive proposal for changing experimental practice so as to promote such stability is put forward, and its implications for explanatory integration are briefly considered.

The aim of this paper is to analyze a philosophical question (neutrality vs. theoryladenness of observation) taking into consideration the empirical results of Cognitive Psychology (theories of perception). This is an important debate because the objectivity of science is at stake. In the Philosophy of Science there are two main positions with regard to observation, those of C. Hempel and N. R. Hanson. In the Philosophy of Mind there are also two important contrasting positions, those of J. Fodor and Paul M. Churchland. I will analyze the consequences of recent theories of perception and vision developed within Cognitive Science for classical epistemological theses about observation.

Neurath's proposal for the form of protocol statements explicates the multiple embedding of a singular sentence as specifying different conditions for the acceptance of such a sentence as a bona fide scientific datum. Before theories are accepted or rejected in the light of such evidence, however, a further condition must be met which Neurath did not formalize. The different conditions are discussed and shown to constitute a naturalistic theory of scientific data and a pragmatic theory of theory acceptance.